Book Image

Mastering IPython 4.0

By : Thomas Bitterman, Dipanjan Deb
Book Image

Mastering IPython 4.0

By: Thomas Bitterman, Dipanjan Deb

Overview of this book

IPython is an interactive computational environment in which you can combine code execution, rich text, mathematics, plots, and rich media. This book will get IPython developers up to date with the latest advancements in IPython and dive deep into interactive computing with IPython. This an advanced guide on interactive and parallel computing with IPython will explore advanced visualizations and high-performance computing with IPython in detail. You will quickly brush up your knowledge of IPython kernels and wrapper kernels, then we'?ll move to advanced concepts such as testing, Sphinx, JS events, interactive work, and the ZMQ cluster. The book will cover topics such as IPython Console Lexer, advanced configuration, and third-party tools. By the end of this book, you will be able to use IPython for interactive and parallel computing in a high-performance computing environment.
Table of Contents (18 chapters)
Mastering IPython 4.0
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
6
Works Well with Others – IPython and Third-Party Tools
Index

Interacting with Python scripts


A simple way to take Python code that already exists and bring it into a notebook is to use the %load magic in a cell:

%load <filename>.p

Running this cell will load the contents of <filename>.py into the current cell:

Running the cell again does not run the script – the point of using %load was simply to include the script on the page, not execute it.

Using the %run magic runs the script and inserts its output into the notebook as the output of that cell:

Tip

Using a notebook with tests

A notebook full of calls to test functions can be a convenient and attractive way to maintain a test suite and records of its results over time.

Of course, if the only thing a notebook did was to allow one to display the output of programs on a web page, it would be of limited usefulness. The real power of Jupyter comes into focus when working with individual cells.